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## Details

Genre/Form: | Electronic books Problems and exercises Problems, exercises, etc |
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Additional Physical Format: | Print version: Little, Roderick J. A. Statistical analysis with missing data. Hoboken, NJ : John Wiley & Sons, Inc., 2020 (DLC) 2018058860 (OCoLC)1080251688 |

Material Type: | Document, Internet resource |

Document Type: | Internet Resource, Computer File |

All Authors / Contributors: |
Roderick J A Little; Donald B Rubin |

ISBN: | 9781118595695 1118595696 |

OCLC Number: | 1090652796 |

Notes: | Includes index. |

Description: | 1 online resource. |

Contents: | Part I Overview and Basic Approaches -- Introduction -- Missing Data in Experiments -- Complete-Case and Available-Case Analysis -- Single Imputation Methods -- Accounting for Uncertainty from Missing Data -- Part II Likelihood-Based Approaches to the Analysis of Data with Missing Values -- Theory of Inference Based on the Likelihood Function -- Factored Likelihood Methods When the Missingness Machanism is Ignorable -- Maximum Likelihood for General Patterns of Missing Data: Introduction and Theory with Ignorable Nonresponse -- Large-Sample Inference Based on Maximum Likelihood Estimates -- Bayes and Multiple Imputation -- Part III Likelihood-Based Approaches to the Analysis of Incomplete Data: Some Examples -- Multivariate Normal Examples, Ignoring the Missingness Mechanism -- Models for Robust Estimation -- Models for Partially Classified Contingency Tables, Ignorning the Missingness Mechanism -- Mixed Normal and Nonnormal Data with Missing Values, Ignoring the Missingness Mechanism -- Missing Not at Random Models. |

Series Title: | Wiley series in probability and statistics. |

Responsibility: | Roderick J.A. Little, Donald B. Rubin. |

### Abstract:

Reflecting new application topics, Statistical Analysis with Missing Data offers a thoroughly up-to-date, reorganized survey of current methodology for handling missing data problems. The third edition reviews historical approaches to the subject and describe rigorous yet simple methods for multivariate analysis with missing values.
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